|Course Dates||Weeks||Meeting Times||Status||Instructor(s)||CRN||Registration|
|June 18, 2018 - June 22, 2018||1||M-F 8:30A-11:20A||Open||Hyeyoung Shin||10641||ADD TO CART|
The human brain is one of the most complicated and mysterious systems on the planet. In recent decades, a huge push has been made to understand the brain through computer modeling. A large number of scientists have been involved in the development of these models not only to advance our understanding and treatments of neurological and psychiatric illnesses, but also to help us understand what underlies daily human experiences ranging from memory to perception to decision making. These models allow scientists to combine results from a variety of other research to try and create a better picture of how the brain works or to reveal gaps in our understanding of the brain. This modeling forms the basis of a field of neuroscience known as computational neuroscience.
The purpose of this course is to twofold: to give students an understanding of how theoretical (computational) neuroscience works in harmony with experimentation to advance our understanding of the brain, and to familiarize students with the MATLAB programming language by learning to create basic models of neurons and neural circuits.
This course will cover a broad range of topics, including:
1. How do the electrical properties of neurons allow them to send information across the nervous system?
2. What types of questions is computational neuroscience best suited to answer? What are the limitations of this method?
This course is ideal for students who are interested in both biological and quantitative sciences. Students will not only be introduced to the field of neuroscience, they will also gain exposure to the history and current state of research on the topic. Furthermore, students will learn to build their own models and develop basic programming proficiency in MATLAB.
In this course, students will learn to do the following:
1. Describe and recognize past and current questions in the field of neuroscience.
2. Identify the advantages and limits of computer modeling in advancing our understanding of the brain.
3. Make rudimentary computational models in MATLAB.
Prerequisites: This course assumes basic proficiency in high school level algebra, though some familiarity with high school biology will be useful. No previous programming experience is required.